For the weighting algorithm of the activation channels, Score-CAM is based on the Channel-wise Increase of Confidence (CIC) measure [1]}, which, for a particular image, is the increase in the target score of the original image that has been masked by a particular channel, as compared to the target score of the baseline unmasked image. Here, the idea is that the target score is improved when certain areas are masked out of the original image [2]}. However, we have found that our target score, which is the probability of cluster assignment fixed between \([0,1]\)  (Equation REF ), rarely improves when certain areas are masked out. Furthermore, if an image \(i\)  is assigned to a particular cluster \(k\)  with probability \(p_{ik}\) , the maximum increase in probability will be \(1-p_{ik}\) ; for high \(p_{ik}\) , the maximum possible increase will be small, which may underestimate the confidence, or importance, of a particular channel. For these reasons, we remove the comparison to the baseline image and define a channel-wise confidence (CC) to weight the activation channels for creating CLAMs, rather than the CIC for Score-CAM. Formally, we have the following definition for CLAM:
